Background Aortic aneurysm (AA) is a life-threatening cardiovascular condition with a strong genetic component, however, its molecular mechanisms remain poorly understood. Although genome-wide association studies (GWAS) have identified numerous risk loci, most prior studies have investigated genetic and metabolic factors separately, leaving the causal pathways from genetic variants to disease largely unexplored. Methods We established an integrative framework combining cross-tissue transcriptome-wide association studies (TWAS) with metabolomic mediation analysis. First, we integrated GWAS data from FinnGen R12 with multi-tissue expression quantitative trait loci (eQTL) data from Genotype-Tissue Expression Project (GTEx) V8, then performed cross-tissue TWAS using the Unified Test for MOlecular SignaTures (UTMOST) and single-tissue validation with the Functional Summary-based Imputation (FUSION) to prioritize susceptibility genes. Second, we applied Mendelian randomization (MR), colocalization, and Fine-mapping Of CaUsal gene Sets (FOCUS) to assess causality and identify high-confidence genes. Third, we performed metabolite mediation analysis to uncover metabolic pathways linking genetic variants to disease risk. Finally, we validated key findings in mouse models of thoracic aortic aneurysm (TAA) and abdominal aortic aneurysm (AAA) using Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction (RT-qPCR) and Western blotting. Results We identified multiple novel susceptibility genes for AA and its subtypes. Key genes included ADH family members (ADH1A, ADH1B, ADH4, ADH6) and ZNF827, which showed cross-subtype associations with strong colocalization evidence in vascular tissues. Metabolite mediation analysis revealed significant pathways involving N-acetylphenylalanine and methionine sulfoxide. Functional enrichment revealed distinct biological mechanisms: AA and AAA were primarily associated with metabolic pathways, whereas TAA-related genes were enriched in developmental and contractile processes. PheWAS indicated no significant off-target associations. Critically, experimental validation in mouse models confirmed significant upregulation of ZNF827 in TAA and ADH6 in AAA at both mRNA and protein levels, corroborating the genetic predictions. Conclusion This integrated cross-omics analysis identifies novel genetic loci and, crucially, uncovers specific nutrient-related metabolic pathways that mediate genetic risk. These findings provide a mechanistic basis for future nutritional and metabolic intervention studies in AA and its subtypes.
Hanxi Wang, Junjie Cheng, Jiali Yao et al.· Frontiers in Nutrition· 0 citations
Analysis of statistical frameworks for multi-omics integration in AD research focuses on approaches that enable causal inference and gene prioritization, with a focus on approaches that enable causal inference and gene prioritization.
Zhuolan Li· Journal of Clinical Technolo...· 0 citations
Background. Type 2 diabetes (T2D) and coronary artery disease (CAD) frequently co-occur, yet the biological pathways that jointly determine risk remain incompletely understood. Most genetic studies have examined shared risk from a single-disease perspective, limiting insight into the mechanisms that generate discordant risk between conditions. Methods. We applied PLACO to multi-ancestry GWAS data of T2D and CAD to identify shared loci, prioritising shared causal signals using colocalisation. Shared variants were clustered by their associations with 77 cardiometabolic traits, and cluster-specific genetic risk scores (GRS) were tested for association with 17 clinical biomarkers and 1,254 binary outcomes in 378,772 UK Biobank (UKB) participants. Two-sample Mendelian randomisation (MR) was used to test the causal role of liver fat. Results. We identified 149 loci shared between T2D and CAD; most novel loci had discordant effects (35 of 42), in contrast to the predominantly concordant signals reported previously. Clustering 187 independent shared variants revealed seven mechanistic clusters, three of them centred on liver fat and defined by discordant T2D?CAD effects. Enrichment analyses and cluster-GRS associations in UKB highlight associations between higher liver fat and T2D risk with a cardioprotective lipid profile and reduced CAD risk. Genetically higher liver fat increased T2D risk but lowered CAD risk in MR analyses; partitioning liver fat instruments by their effect on ApoB-containing lipoproteins indicates that the CAD effects are determined more by effects of circulating ApoB rather than liver fat itself. Conclusions. Liver fat largely sets the direction of T2D risk, whereas the fate of that lipid, retained in the liver with low circulating ApoB or exported as ApoB-containing lipoproteins, sets the direction of CAD risk. This liver-centric partitioning provides a mechanistic framework for the discordant cardiometabolic effects of hepatic lipid and lipid-lowering pathways, with implications for precision prevention.
X. Jiang, N. HirschmuÌller, H. Taylor et al.· medRxiv· 0 citations
Background Coronary atherosclerosis (CA) is a leading cause of cardiovascular morbidity and mortality worldwide. This study is aimed at identifying candidate plasma proteins and potential therapeutic targets for CA. Methods We performed a proteome‐wide Mendelian randomization (MR) analysis using integrated protein quantitative trait loci (pQTLs) and genome‐wide association study (GWAS) summary data. Forward two‐sample MR was first performed using cis‐pQTLs from the UK Biobank Pharma Proteomics Project (UKB‐PPP), followed by reverse MR analysis to exclude potential reverse causality. Bayesian colocalization analysis was conducted to ensure that the associations between proteins and CA were driven by shared genetic variants. Summary‐data‐based MR (SMR) combined with HEIDI testing was used to prioritize proteins and eliminate linkage bias. Significant proteins were cross‐referenced with a curated druggable genome to identify their potential therapeutic relevance. Cross‐platform validation was performed using the SomaScan‐based pQTL dataset from deCODE genetics. An oxidized low‐density lipoprotein (ox‐LDL)–induced human umbilical vein endothelial cell (HUVEC) injury model was used for the evaluation of prioritized proteins. Results Forward MR analysis using UKB‐PPP cis‐pQTL data identified 45 CA‐associated proteins (23 protective, 22 risk‐related; FDR < 0.05), with no reverse causality observed. Five proteins—PARP1, SDCCAG8, FST, FOLH1, and NCAN—were prioritized through MR (FDR < 0.05), colocalization analysis (PP.H4 > 0.50), and SMR analysis with HEIDI filtering (p_SMR < 0.05; p_HEIDI > 0.05). All five proteins were included in the druggable genome list, supporting their potential therapeutic relevance. PARP1 showed consistent associations across Olink and SomaScan platforms and was upregulated in an ox‐LDL‐induced HUVEC model as assessed by western blot. Conclusions This study identified PARP1, SDCCAG8, FST, FOLH1, and NCAN as genetically prioritized candidate proteins for CA, with PARP1 showing the most consistent evidence across analyses. Further validation and mechanistic studies are warranted.
Da Gao, Hai-Yan Lin, Sheng-Jie Wang et al.· Cardiovascular Therapeutics· 0 citations
Background Diabetic retinopathy (DR) and Alzheimer disease (AD) share metabolic and vascular dysfunctions, but the extent to which they reflect overlapping genetic susceptibility and neurovascular-metabolic regulatory pathways remains unclear. We combined multi-omics analyses with population-based data to examine the genetic convergence, cellular pathways, and longitudinal association between DR and AD. Methods We performed a two-sample Mendelian randomisation (MR) to estimate the association between genetically predicted DR liability and AD risk. We used Bayesian colocalisation analysis to identify shared genomic loci, and summary-data-based MR (SMR) to detect expression-mediated genes jointly associated with DR and AD. We analysed single-cell RNA sequencing data to characterise shared cellular features and related biological pathways. We also conducted an MR-based mediation analysis to explore whether lipid-related, metabolic, or inflammatory traits mediated the observed DR-AD association, and a longitudinal analysis of the UK Biobank cohort to assess the association between DR and incident AD. Results With the MR analysis, we found that genetically predicted liability to DR was associated with a modest increase in AD risk. Colocalisation analysis supported a shared genetic signal. We identified three genes with shared expression-mediated associations across DR and AD through SMR. Functional enrichment analyses revealed partially overlapping neurovascular and metabolic pathways. Using MR-based mediation analysis, we found no significant intermediary traits linking DR and AD. Findings from the UK Biobank cohort were directionally consistent with the genetic analyses. Conclusions Genetic liability to DR is associated with an increased risk of AD and is accompanied by shared expression-mediated effects and convergent neurovascular-metabolic pathways. These findings support the possibility that DR may serve as a clinically accessible indicator of increased neurodegenerative vulnerability.
Jing Li, Qian Liu, Qian Ma et al.· Journal of Global Health· 0 citations
OBJECTIVES
Hypertension is highly prevalent in Asian populations and represents a major cardiovascular risk factor. However, most genome-wide association studies (GWASs) and transcriptome-wide association studies (TWASs) have focused primarily on Caucasian cohorts. This study aimed to identify genetic loci and gene expression signatures associated with hypertension in an Asian population.
METHODS
We analyzed 10 739 hypertensive patients and 49 668 controls from the Taiwan Biobank, testing 4 512 191 genome-wide single nucleotide polymorphisms (SNPs). Integrated GWAS, TWAS, and expression quantitative trait locus (eQTL) analyses were conducted to characterize genetic risk. Additionally, a polygenic risk score (PRS) was constructed using a split-sample design to evaluate genetic risk stratification.
RESULTS
We identified 14 loci significantly associated with hypertension, including a novel locus at 5p13.1. eQTL analysis linked this locus to DAB2 expression in whole blood. TWAS detected 55 hypertension-associated genes, with 20 (36%) overlapping GWAS loci. Several novel genes outside GWAS loci, including FBXL15, KCNIP2, and CRIP3, were highly significant and implicated in vascular biology and hypertension mechanisms. PRS analysis effectively differentiated hypertension risk, with individuals in the top 10% showing a > 3.5-fold increased risk compared to the bottom 10%.
CONCLUSIONS
Our findings provide new insights into the genetic and transcriptomic landscape of hypertension in Asians. The identification of novel loci and genes advances understanding of disease biology and may guide precision medicine approaches for risk prediction and therapeutic development.
Sheng-Nan Chang, Guan-Wei Lee, J. Chen et al.· Journal of Hypertension· 0 citations
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